367 machine-learning "https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" research jobs at Nature Careers
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will develop atomistic models and machine-learning potentials to interpret experimental data and predict catalytic performance. The tasks can include Advancing equivariant neural network potentials
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, disability, age, ancestry, military service, protected veteran status, or other characteristics protected by law. Pay Transparency Statement The hiring range is based on market pay structures, with individual
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machine learning techniques, will quantify groundwater recharge and groundwater resilience. Your responsibilities: Analyse the dynamics of hydrological connectivity of soil moisture using gridded soil
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analysing multimodal deep learning models for time-specific cancer risk and time-to-event prediction by integrating imaging with longitudinal Electronic Health Record (EHR) signals. Building scalable
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machine learning methods are a plus. Qualifications: PhD in neuroscience, or related fields DeepLabCut or similar methods Demonstrated hands-on experience with 2-photon imaging techniques Experience
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), proteomics (LC-MS/MS), (epi)genomic data processing, multi-omics integration, machine learning approaches for high-dimensional data, confocal / two-photon imaging, tissue clearing and light-sheet microscopy
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Engineering or a related field The ideal candidate should have some knowledge and experience in the following topics: Software Cybersecurity Software Testing and Analysis Machine Learning and Multimodal Large
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information, military service, or other protected status.
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key agroecosystem variables. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and
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, ATAC-seq, CUT&RUN, MERFISH, Visium), epigenomic data processing (chromatin accessibility, histone marks, enhancer mapping), multi-omics integration using Seurat, Signac, Harmony, ArchR or Scanpy, machine